This thesis focuses on analysing the Dutch dairy farmer behaviour in a changing political environment. The general objective of this research is to analyse the responses of Dutch dairy farmers in the situation of a changing agricultural and environmental policy context (i.e. changes in the subsidy payment system, milk quota abolishment and the reformed Dutch manure policy), thereby taking into account economic as well as non-economic factors. In order to study the research questions, yearly data (from the period 2001 to 2012) on various economic and non-economic variables were gathered.

The analysis methods used are (the evaluation of) an economic simulation experiment, literature study and econometrics. Generally it is found that active Dutch dairy farmers, which are expected to continue farming in the future, followed an expansion strategy. Although the dairy farmers were facing different agricultural policy regulations, their farmer behaviour was almost consistent over the years.

Dairy in Europe has undergone many changes in the last few years—the abolition of milk production quotas being a fundamental one. This study explores these changes in relation to the sustained social and environmental viability of the sector and how dairy processors' sustainability programs are a part of that.

Regime change as outlined in transition theory enhanced through a sociological approach on actors informed this research. More specifically, the notion of obligatory passage points was used to explore the mechanisms through which dominant actors make certain actions mandatory and reify their status as indispensable. The thesis consists of three case studies: the dairy sectors in the Netherlands, Ireland and the United Kingdom. The cases trace the evolution of all sectors since the post-war era, outlining the dominant logic that has guided its development. The sustainability programs of three dairy processors—located in each of the case countries—are also part of the analysis. Data was collected through document analysis and semi-structured interviews.

The analysis shows that the post-war logic based on the increase of scale and intensification of dairying has continued to shape the development of the sector through today. While the visible impacts of intensive dairy have led to adaptations to the dominant rules and practices, these changes have not been fundamental in nature. The analysis of dairy processors and their sustainability programs revealed that these programs can be an additional tool for compliance to legal standards and the alleviation of pressing societal concerns. However, processors address social and environmentally relevant dairy-related challenges when an effective link to profit can be established. These programs have been unable to ensure that the dairy sector operates within established environmental limits and societal expectations, while providing a stable livelihood for farmers.

This research contributes to the understanding of sustainability (agri-food) transitions by identifying the mechanisms through which the regime adapts to the shifting environment and dominant actors strive for their own continuity. It also adds to the debate about the role that incumbent actors can have in sustainability transitions—their involvement is important but they are unable to guide such processes. This study advances the empirical ground in sustainability transition studies by focusing on systems in which change is less likely to be technologically driven and where social change plays a larger role. Finally, this thesis connects past development, current challenges, and present engagement in a discussion about the future development of the dairy sector; this adds to the further conceptualization of the complexity and co-evolutionary nature of sustainability transitions.

Since the 1980s, efforts have been made to develop sensors that measure a parameter from an individual cow. The development started with individual cow recognition and was followed by sensors that measure the electrical conductivity of milk and pedometers that measure activity. Some sensors like activity meters, electrical conductivity, weight floors and somatic cell count sensors are commercially available. Adoption has in general been low and mainly driven by the AMS, with a clear exception for estrus detection. In practice, the economic benefits of using sensor systems has not been proven. So, to make sensors live up to their full potential there is a need for research to shift from technical development towards practical applications and integration with operational farm management. Estrus detection sensors can have a good detection performance and are currently applied by farmers in practice, therefore this thesis focusses on sensors that support reproductive management. The main objective of this thesis is to study the utility of sensor technology to support reproductive management on dairy farms. This main objective was split in five sub objectives that each study a part of the main objective and were discussed in the separate chapters of this thesis.

We demonstrated that utility of sensors for reproductive management can be found in economic benefits (estrus and calving detection), reduction of labor (calving and estrus detection) and more detailed management information (prognosis of insemination success). So, automated estrus detection aids reproductive management.

From this thesis the following conclusions can be drawn:

The developed theoretical framework describes four levels of sensor development, which should all be included in proper development of sensor systems. The literature review showed that no studies developed sensor systems with regard to management and decision support.

It was possible to improve the prediction of the start of calving compared to a model that only uses the expected calving date. However, predicting the start of calving within an hour was not possible with a high sensitivity and specificity.

There was financial merit in the use of calving detection, because the sensor system enables more timely intervention by the farmer. The uncertainty about the positive effects was large, which caused a wide range in the simulated financial benefits.

Investment in a sensor for estrus detection was on average profitable with a return on investment of 11%. Profitability was influenced most by the heuristic culling rules and the expected increase of the estrus detection rate between detection by visual observation and the sensor.

Routinely collected farm data can be used to estimate a prognosis on insemination success and be used to determine whether an individual cow has a higher or lower than average likelihood of insemination success. Integration of this prognostic model with an estrus detection sensor has potential.

Currently farmers only adopt sensors for estrus detection or because they were standard with an AMS. A reason for this is that sensor systems do not produce clear information for farmers. Sensor technology should be focused on management support of applications. Labor benefits of sensors are important for adoption of sensors by farmers, farmers value flexibility, increased family time and less physical workload as benefits. However, economic evaluations of technical solutions are unable to quantify these benefits. Sensor research should consider the preference of farmers regarding labor. For the appraisal of sensor technology new methods to value labor benefits of sensor are needed. Furthermore, in sensor development societal acceptance should be an important consideration. Animal rights activists may frame the use of sensors as a form of industrialized farming. Only using technical arguments and considerations to explain the benefits of sensors will hamper the societal acceptance of modern dairy farming. Application of sensors on dairy farms should be communicated smartly to society in terms that relate the values of citizens.

Improved reproductive performance has a substantial benefit for the overall profitability of dairy cattle farming by decreasing insemination and veterinary treatment costs, shortening calving intervals, and lowering the rate of involuntary culling. Unfortunately, the low heritability of classical fertility traits derived from calving and insemination data makes genetic improvement by traditional animal breeding slow. Therefore, there is an interest in finding novel measures of fertility that have a higher heritability or using genomic information to aid genetic selection for fertility. The overall objective of this thesis was to explore the use of milk progesterone (P4) records and genomic information to improve selection for fertility in dairy cows. In a first step, the use of in-line milk progesterone records to define endocrine fertility traits was investigated, and genetic parameters estimated. Several defined endocrine fertility traits were heritable, and showed a reasonable repeatability. Also, the genetic correlation of milk production traits with endocrine fertility traits were considerably lower than the correlations of milk production with classical fertility traits. In the next step 17 quantitative trait loci (QTL) associated with endocrine fertility traits, were identified on Bos taurus autosomes (BTA) 2, 3, 8, 12, 15, 17, 23, and 25 in a genome-wide association study with single nucleotide polymorphisms. Further, fine-mapping of target regions on BTA 2 and 3, identified several associated variants and potential candidate genes underlying endocrine fertility traits. Subsequently, the optimal use of endocrine fertility traits in genomic evaluations was investigated; using empirical and theoretical predictions for single-trait models, I showed that endocrine fertility traits have more predictive ability than classical fertility traits. The accuracy of genomic prediction was also substantially improved when endocrine and classical fertility traits were combined in multi-trait genomic prediction. Finally, using deterministic predictions, the potential accuracy of multi-trait genomic selection when combining a cow training population measured for the endocrine trait commencement of luteal activity (C-LA), with a training population of bulls with daughter observations for a classical fertility trait was investigated. Results showed that for prediction of fertility, there is no benefit of investing in a cow training population when the breeding goal is based on classical fertility traits. However, when considering a more biological breeding goal for fertility like C-LA, accuracy is substantially improved when endocrine traits are available from a limited number of farms.

The EU dairy sector is facing a crisis, which also affects Dutch dairy farmers. Low milk prices have negatively affected dairy farm profitability. At the same time, the structural adjustment in the Dutch dairy sector has slowed down: the reduction in the rate of farm exits was below normal levels and in contrast with the pattern observed in several other EU Member States. Now the Dutch government would like to consider a temporary support programme aimed at restructuring the dairy sector. The Ministry of Economic Affairs has requested Wageningen Economic Research to provide a background analysis with respect to such a temporary measure. This analysis is requested because the proposed measure would imply state aid to the Dutch dairy sector, which is only allowable in case a number of criteria are satisfied. This research should provide insight into this matter.